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View Code? Open in Web Editor NEWMeta learning with BERT as a learner
Meta learning with BERT as a learner
请问为什么会常出现Segmentation fault (core dumped) 这样的问题呢?是因为梯度设置的问题吗,期待你的回复🥹
作者你好,感谢你提供的bert meta learning的实现代码。
我在阅读reptile这部分代码的时候有一个问题:在reptile.py计算梯度的部分(第90行) gradient = meta_params - fast_params,为什么不是用更新后的模型参数减去更新前参数呢?我试着把他们的位置调换,发现对模型效果影响并不大,但是按照相反方向更新模型应该会训不动的。
另外,为什么outer learning rate 要设一个这么小的值呢(5e-5),本来inner learning rate已经很小了,如果一个小的outer learning rate 乘以平均后的梯度,那么更新的程度不会很小吗?
期待回复,谢谢!
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